Researchers from multiple universities have addressed the challenge of designing large-scale DNN chiplet accelerators, focusing on optimizing monetary cost (MC), performance, and energy efficiency. The complexity arises from the interplay of various parameters,...

This article features this new deep learning framework, RustBurn, which was developed entirely in the Rust programming language. The core principles of flexibility, performance, and ease of use drive rust Burn. Flexibility is a pivotal feature of Rust Burn, enabling...

In Large Language Models (LLMs), models like ChatGPT represent a significant shift towards more cost-efficient training and deployment methods, evolving considerably from traditional statistical language models to sophisticated neural network-based models. This...

The increasing reliance on cloud-hosted large language models for inference services has raised privacy concerns, especially when handling sensitive data. Secure Multi-Party Computing (SMPC) has emerged as a solution for preserving the privacy of both inference data...

Language models are playing the most crucial role in natural language processing, and their development and optimization are essential for achieving accurate and effective outcomes. The trend has gravitated towards creating voluminous and intricate models to enhance...

Adversarial attacks in image classification, a critical issue in AI security, involve subtle changes to images that mislead AI models into incorrect classifications. The research delves into the intricacies of these attacks, particularly focusing on multi-attacks,...